I put together an experiment to compare different classification machine learning algorithms in real time to gain insight into which ones handle certain situations better than others: http://jsfiddle.net/wybiral/3bdkp5c0/embedded/result/

Currently the algorithms covered are:

As the algorithm trains you'll see the background color morph to display the classification boundary. Change the algorithm (via the dropdown on the top) and see how it impacts the classification boundary.

Currently the algorithms covered are:

- Linear regression (with cubic expansion on feature space)
- Logistic regression (with cubic expansion on feature space)
- Neural network (sigmoidal feed forward back propagation)
- K nearest neighbor (where k=5)
- Naive bayes
- Support vector machine (gauss kernel)
- Discriminate analysis

As the algorithm trains you'll see the background color morph to display the classification boundary. Change the algorithm (via the dropdown on the top) and see how it impacts the classification boundary.

## Comments

What is the nerdy.js library? There's only the minified version in the fiddle

Thanks

I've thought about polishing it a bit and releasing it to the open source community, but I'm not sure what kind of demand there is for machine learning in Javascript.